code: def make_parser():
      parser = options.get_speech_generation_parser()
      parser.add_argument("--dump-features", action="store_true")
      parser.add_argument("--dump-waveforms", action="store_true")
      parser.add_argument("--dump-attentions", action="store_true")
      parser.add_argument("--dump-eos-probs", action="store_true")
      parser.add_argument("--dump-plots", action="store_true")
      parser.add_argument("--dump-target", action="store_true")
      parser.add_argument(
          "--output-sample-rate", default=22050, type=int
      )
      parser.add_argument("--teacher-forcing", action="store_true")
      parser.add_argument(
          "--audio-format",
          type=str,
          default="wav",
          choices=["wav", "flac"],
      )
      return parser
  
file_path: fairseq/examples/speech_synthesis/generate_waveform.py
imports: import ast
  import logging
  import matplotlib.pyplot
  import numpy
  from pathlib import Path
  import soundfile
  import sys
  import torch
  import torchaudio
  from fairseq import checkpoint_utils, options, tasks, utils
  from fairseq.logging import progress_bar
  from fairseq.tasks.text_to_speech import plot_tts_output
  from fairseq.data.audio.text_to_speech_dataset import TextToSpeechDataset
label_desc: Use image node_id 1 for calling a global function with example usage: make_parser() and returns: parser